Магистратура
2024/2025




Аналитические инструменты управления финансами предприятия
Статус:
Курс обязательный (Финансы)
Направление:
38.04.08. Финансы и кредит
Кто читает:
Департамент финансов
Где читается:
Санкт-Петербургская школа экономики и менеджмента
Когда читается:
1-й курс, 4 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Прогр. обучения:
Финансы
Язык:
английский
Кредиты:
3
Course Syllabus
Abstract
The purpose of the discipline is to form the student's knowledge of analytical methods of tools in the management of enterprise finances. As part of the course, students will study decision-making methods in various functional areas of enterprise finance, as well as methods and algorithms for quantitative assessments of the processes of providing enterprise activities with financial resources. The main goal of the course is to familiarize with modern approaches to modeling and optimization of financial operations and functions, approaches to the problem of making economically sound decisions in conditions of uncertainty.
Learning Objectives
- Introduction to relational database management systems with MS SQL Server as an example
- Learning solid basis of SQL querying
- Exploring Window Functions
- Acquiring bases in Pandas and Numpy for data transformation, including Effective Pandas, as well as simple data visualization
Expected Learning Outcomes
- Analyse financial and non-financial statements to select metrics for building the financial model.
- Apply Regression Tools to make Predictions, and improve Forecasts with Multiple Regression.
- Ability to write SQL queries in a relational DBMS
Course Contents
- Lecture 1. MS SQL Server and SQL foundations.
- Lecture 2. Single-Table Queries, Data types and built-in functions
- Lecture 3. Table Joins and Set operators.
- Lecture 4. Subqueries and table expressions.
- Lecture 5. Window functions.
- Lecture 6. Crash course into Pandas and Numpy
- Lecture 7. Effective Pandas.
- Lecture 8. Data visualization in Python.
Interim Assessment
- 2024/2025 4th module0.5 * Final Examination + 0.25 * In class test 1 + 0.25 * In class test 2
Bibliography
Recommended Core Bibliography
- McKinney, W. (2012). Python for Data Analysis : Data Wrangling with Pandas, NumPy, and IPython. Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=495822
- McKinney, W. (2018). Python for Data Analysis : Data Wrangling with Pandas, NumPy, and IPython (Vol. Second edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1605925
Recommended Additional Bibliography
- Date, C. J. (2015). SQL and Relational Theory : How to Write Accurate SQL Code (Vol. Third edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1099367